Current diabetes reviews最新文献

Diabetes is a chronic, irreversible, non-infectious metabolic syndrome associated with low insulin production by the pancreas or due to insulin resistance. The management landscape for diabetes is swiftly evolving due to ongoing advancements. Conventional treatment approaches have struggled to fully address the root causes of the disease while also carrying significant risks of adverse effects. Flavonoids are an extensive class of phytonutrients present in grains, vegetables, fruits, cocoa, tea, wine, and nuts. Many studies have reported that flavonoids have shown diversified pharmacological activity in recent years. Thus, this review will give you an overview of the significant anti-diabetic potential of promising flavonoids. Various search engines such as PubMed, Scopus, Google Scholar, and WoS have been explored by using the keywords "apigenin," "luteolin," "naringenin," "hesperidin," "kaempferol," "quercetin," "myricetin" and "taxifolin" with "anti-diabetic." The anti-diabetic activity of flavonoids is attributed to various mechanisms, including α glucosidase, α-amylase inhibitory effects, GLUT4 expression, antioxidant, and apoptosis. However, their inadequate biopharmaceutical qualities make their effectiveness in clinical translation constrained. This review aims to highlight plant-derived flavonoids through in-vitro, in- -vivo, and clinical insights. Additionally, the review highlights the recent advancement in the drug delivery system in diabetes to overcome the limitation of flavonoids.

Background: Diabetic retinopathy (DR) is a persistent microvascular complication associated with diabetes, and it constitutes a significant cause of visual impairment and blindness.

Aims: This study aimed to assess the correlation between serum bilirubin levels and the prevalence of DR in patients diagnosed with type 2 diabetes mellitus (T2DM). Additionally, we sought to establish whether the polymorphisms of Nuclear Factor E2-Related Factor 2 (Nrf2) might modify this relationship.

Methods: A cross-sectional study was undertaken in Jiangxi, China, from May, 2012 to December, 2014. Serum bilirubin levels were assessed in 558 subjects, and the correlation between bilirubin and DR was analyzed using generalized linear models with a logit link. The study utilized odds ratios (OR) and 95% confidence intervals (CI) to evaluate the relationship, both with and without the consideration of clinical risk factors.

Results: There was a significant inverse association between serum total bilirubin (TBiL) and the risk of DR (per 1-μmol/L increment; OR, 0.89; 95% CI: 0.84-0.94). Accordingly, when TBiL was categorized into tertiles, individuals in tertiles 2 and 3 exhibited significantly lower risks of DR compared to those in tertile 1. The OR for these tertiles was 0.54 (95% CI: 0.34-0.87) and 0.31 (95% CI: 0.19-0.52), respectively. Moreover, a stronger inverse relationship between TBiL and DR was observed in individuals carrying the CC and AC genotypes compared to those with the AA genotype. The OR for individuals with the CC/AC genotype was 0.87 (95% CI: 0.82, 0.92), while that for the AA genotype was 1.17 (95% CI: 0.95, 1.45). This difference was statistically significant (p for interaction = 0.001).

Conclusion: There was a significant inverse association between bilirubin and DR in participants with CC or AC genotype. However, this inverse association was not seen in AA genotype participants.

Background: Recent research demonstrates that diabetes can lead to heart problems, neurological damage, and other illnesses.

Method: In this paper, we design a low-complexity Deep Learning (DL)-based model for the diagnosis of type 2 diabetes. In our experiments, we use the publicly available PIMA Indian Diabetes Dataset (PIDD). To obtain a low-complexity and accurate DL architecture, we perform an accuracy-versus-complexity study on several DL models.

Result: The results show that the proposed DL structure, including Convolutional Neural Networks and Multi-Layer Perceptron models (i.e., CNN+MLP model) outperforms other models with an accuracy of 93.89%.

Conclusion: With these features, the proposed hybrid model can be used in wearable devices and IoT-based health monitoring applications.

Introduction: Type 2 Diabetes Mellitus (T2DM) accounts for more than 95% of all diabetes cases and is a leading cause of disability and death. This study aimed to evaluate the effectiveness and safety of a combination therapy involving metformin, teneligliptin, and glimepiride in patients diagnosed with T2DM.

Methods: The present quasi-experimental clinical trial involved 300 adult T2DM patients. They were divided into three groups: Group 1 (Metformin; n=100), Group 2 (Metformin + Teneligliptin; n=100), and Group 3 (Metformin + Teneligliptin +; n=100). Along with demographic data, we collected information on HbA1c, FBS, and PPBS levels, as well as fasting insulin, CPeptide, HOMA-IR, QUICKI-IR, and lipid, renal, and hepatic profiles at baseline and after 3, 6, and 12 months. Data analysis was performed using SPSS 21.0 software.

Results: A total of 300 patients participated in the study. At the end of 12 months, triple-drug therapy achieved significant glycemic control (HbA1c: 6.56±0.50%; P<0.0001) and reduced FBS (7.6±1.41 mg/dl; P<0.0001), PPBS (9.39±2.14 mg/dl; P<0.0001), and fasting insulin (11.26±2.5 IU; P<0.0001), C-peptide (2.01±2.29 ng/ml; P<0.0001), and insulin resistance by HOMA-IR (3.74±0.7; P<0.0001). Favorable lipid profiles (P<0.0001) were noted versus other groups. Despite renal and hepatic profile variations, values remained within the normal range.

Conclusion: The combination of teneligliptin with metformin and glimepiride in T2DM patients demonstrated significant improvements in glycaemic control, reduced insulin resistance, and positive effects on lipid, renal, and hepatic profiles. Importantly, the therapy did not result in serious adverse drug reactions, such as hypoglycemia. We need more RCTs to substantiate these findings.

Type 2 Diabetes Mellitus (T2DM) is a chronic metabolic disorder characterized by chronic hyperglycemia, which often co-exists with other metabolic impairments. This condition can damage various tissues and organs, resulting in the development of severe complications, both microvascular, such as retinopathy, nephropathy, and neuropathy, and macrovascular, responsible for an increased risk of cardiovascular diseases. Curcumin is the main bioactive molecule found in the rhizomes of turmeric. Many studies have reported curcumin to exhibit antioxidant, anti-inflammatory, anti-infectious, and anti-cancer properties; thus, there is an increasing interest in exploiting these properties in order to prevent the rise or the progression of T2DM, as well as its possible associated conditions. In this review, we have presented the current state-ofart regarding the clinical trials that have involved curcumin administration and analyzed the possible mechanisms by which curcumin might exert the beneficial effects observed in literature.

Diabetic chronic wounds and amputations are very serious complications of diabetes mellitus (DM) that result from an integration factor, including oxygen deprivation, elevated reactive oxygen species (ROS), reduced angiogenesis, and microbial invasion. These causative factors lead to tenacious wounds in an inflammatory state, which eventually results in tissue aging and necrosis. Wound healing in DM potentially targets C-X-C chemokine receptor type 4 (CXCR4) regulates several signalling pathways. The CXCR4 signalling pathway integrated with phospholipase C (PLC)/protein kinase-C (PKC) Ca2+ pathways, stromal cell-derived factor-1 (SDF-1), and mitogen- activated protein kinases (MAPKs) pathway for enhancing cell chemotaxis, proliferation, and survival. The dysregulated CXCR4 pathway is connected with poor wound healing in DM patients. Therapeutic strategies targeting CXCR4-based molecules such as UCUF-728, UCUF-965, and AMD3100 have been shown to enhance diabetic wound healing by altering miRNA expression, promoting angiogenesis, and accelerating wound closure. This study indicates that CXCR4 participation in various signalling pathways makes it essential for Understanding the healing of diabetic wounds. Using specific compounds to target CXCR4 offers a potentially effective treatment strategy to improve wound healing in diabetes. Our understanding of CXCR4 signalling and its regulation processes will enable us to develop more potent wound care solutions for diabetic chronic wounds. This report concludes that CXCR4's potential therapeutic targeting shows improvements in diabetic wound repair. This review will demonstrate that CXCR4 plays a major role in wound healing through its various signalling pathways. Targeting CXCR4 with certain agonist molecules shows a therapeutic approach to potentially increasing wound healing in diabetes. By enhancing our understanding of the CXCR4 signalling mechanism in future studies, we can develop more potential treatments for chronic diabetic wounds.

Objective: The aim of this study was to assess how the lockdown of the COVID-19 pandemic had affected the glycaemic control of adolescents aged 10-19 with type 1 diabetes.

Methods: A comprehensive search of literature was performed in PubMed, Scopus, Web of Science, and ProQuest. Published articles up to September 2022 were included. The Glucose Monitoring Index (GMI) and HbA1c level were defined as outcome variables. Average glucose level was found to be a common variable in both HbA1c levels and GMI; therefore, HbA1c and GMI were converted to average glucose (mg/dL) using appropriate formulas. Studies reported the outcomes in two or three periods (pre-lockdown, lockdown, and post-lockdown) were included in the analysis. A paired wise meta-analysis was performed among the studies that reported all three periods. Homogeneity across studies was assessed using I2 statistic.

Result: Fourteen studies were included in the study. The pooled average glucose during the lockdown decreased to 166.9 mg/dL (95% CI, 153.78, 180.02) from 205.793 mg/dL (95% CI, 188.412, 223.173) during the pre-lockdown period, then it increased to 204.23 mg/dL (95% CI, 186.17, 222.29) during the post-lockdown period. A paired wise meta-analysis indicated a reduction in average glucose levels. However, it was not statistically significant, possibly due to the small number of studies that reported data from all three periods.

Conclusion: Although the descriptive analysis of our study showed that the lockdown had affected (decreased) the average glucose level among adolescents with type 1 diabetes, this was not statistically significant in the pooled analysis.

Diabetic retinopathy (DR) is a complication of diabetes mellitus which causes retinal damage which when left untreated will cause visual problems. As the prevalence of DR increases over the years, there is a need to optimise the currently available treatments as well as developing novel drugs to improve the therapy provided for the patients in the clinical practice. Several pharmacological therapies like, anti-vascular endothelial growth factor and anti-inflammatory therapies which include intravitreal, and implant of corticosteroids are significant in the management to decrease the risk of DR-related vision impairment. Clinical trials for novel drug therapies are still ongoing till this day to enhance the efficacy of DR treatment. Even though there are also modern treatments such as laser therapy for the patients, prevention should be done to lower the number of individuals affected by DR. Due to the complexity of DR, there are numerous obstacles to develop new medications for DR which include the increasing healthcare cost of DR treatment. New insights such as utilisation of artificial intelligence will be implemented into the management of DR as it has proved its potential in aiding the screening process. In parallel with the increase in DR prevalence and the number of treatments developed, extensive understanding of the mechanism of action of DR should be further improved to prevent more complications in the future. This review summarises the epidemiological trend, prevention strategies, challenges in treatment, current novel therapeutics (including drugs under clinical trials), future therapeutic trends and possibilities for implementing AI in the early diagnosis and management of DR.

Background: Diabetic peripheral neuropathy (DPN) is the prevalent microvascular complication of diabetes mellitus (DM). 30-50% of diabetics are likely to be affected by DPN. It significantly impacts the skeletal muscles, resulting in an accelerated loss of muscle mass. The objective of this systematic review was to evaluate the ankle and foot muscle changes in diabetic peripheral neuropathy using ultrasound.

Method: A comprehensive search was conducted in Scopus, Embase, and PubMed databases, which yielded 64 studies, out of which 5 studies are included in this meta-analysis.

Result: The meta-analysis shows that the thickness and cross-section area of the extensor digitorum brevis muscle are reduced in DPN as compared to the control group with p-value<0.004 and p-value<0.001, respectively. The thickness of MIL muscle was also smaller in DPN p-value=0.02. Similarly, the thickness and CSA of AH muscle are also reduced in DPN patients compared to the control group, with p-values of 0.21 and 0.14.

Conclusion: Meta-analysis reveals that diabetic peripheral neuropathy (DPN) patients have reduced foot muscle thickness and cross-sectional area (CSA) compared to controls without neuropathy. This highlights the importance of ultrasound in detecting muscle atrophy early in diabetic patients since it provides objective measures beyond traditional screening with its real-time and non-invasive nature.

Background: Brevifoliol is a diterpenoid that occurs naturally in the plants of Taxus genus and is widely used as chemotherapy agent for the management of cancer. A series of semisynthetic esters analogues of brevifoliol were prepared by Steglich esterification and attempted for their pharmacological potential against insulin resistance conditions using in-vitro and in-silico assays.

Objective: The aim of this study is to understand the pharmacological potential of eighteen semisynthetic analogs through Steglich esterification of Brevifoliol against insulin resistance condition Methods: In the in-vitro study, insulin resistance condition was induced in skeletal muscle cells using TNF-α, pro-inflammatory cytokine and these cells were treated with brevifoliol analogues. The most potent analouge was further validated using in-silico docking study against the tumor necrosis factor (TNF-α) (PDB ID: 2AZ5) and Human Insulin Receptor (PDB ID: 1IR3), using the Auto dock Vina v0.8 program.

Results: Although, all the analogues of Brevifoliol significantly exhibited the pharmacological potential. Among all, analogue 17 was most potent in reversing the TNF-α induced insulin resistance condition in skeletal muscle cells and also to inhibit the production of TNF-α in LPSinduced inflammation in macrophage cells in a dose-dependent manner. Similarly, in-silico molecular docking studies revealed that analogue 17 possesses a more promising binding affinity than the selected control drug metformin toward the TNF-α and insulin receptor.

Conclusion: These findings suggested the suitability of analogue 17 as a drug-like candidate for further investigation toward the management of insulin resistance conditions.